ML Infra Engineer: Kubernetes & Scalable Data Platforms

MOTIONAL SINGAPORE PTE. LIMITED; Singapore; On-site; SGD 80,000 - 130,000; Full time

Job summary

MOTIONAL SINGAPORE PTE. LIMITED is seeking a software engineer to help build and operate the ML infrastructure powering self-driving technology.

You will design and deploy core platform components on Kubernetes, working across data ingestion, processing, and model evaluation to support the entire ML lifecycle. Ideal candidates have 2+ years of professional software engineering experience, a degree in CS, hands-on Kubernetes, and strong Python/Go skills, with experience on AWS, GCP, or Azure.

Qualifications

• 2+ years of professional software engineering experience.
• BS or MS in Computer Science or a related technical field.
• Hands-on experience developing and deploying applications on Kubernetes (k8s).
• Experience building or working on high-scale infrastructure or distributed backend systems.
• Strong proficiency in Python, Go, or a similar language.
• Solid experience with a major cloud provider (AWS, GCP, Azure).

Responsibilities

• Design, build, and deploy core components of our ML infrastructure platform on Kubernetes.
• Develop robust and scalable services that support the entire ML lifecycle, from data ingestion and processing to model training and evaluation.
• Write high-quality, maintainable code for high-throughput systems that handle petabytes of data.
• Own features and systems end-to-end, driving them from initial design through to production deployment and operation.

Skills

Kubernetes

Python

Go

Cloud providers

Education

Bachelor’s or Master’s in Computer Science

Tools

Kubernetes (k8s)

Ray (Data/Train)

GPU orchestration

Job description

MOTIONAL SINGAPORE PTE. LIMITED is seeking a software engineer to help build and operate the ML infrastructure powering self-driving technology.

You will design and deploy core platform components on Kubernetes, working across data ingestion, processing, and model evaluation to support the entire ML lifecycle. Ideal candidates have 2+ years of professional software engineering experience, a degree in CS, hands-on Kubernetes, and strong Python/Go skills, with experience on AWS, GCP, or Azure.